Business intelligence & analytics today have dramatically shifted from the traditional IT-driven model to a modern self-service approach. This is due to a number of changes, including the fact that the balance of power has steadily shifted from IT to the business, and also the fact that the business community has new access to more innovative technologies that give them powerful analytical and visualization capabilities (e.g. Tableau, …).  This increased use and capability has put the business in the driver seat of much front-end BI decision-making. 

In order to help your business community continue to increase its self-service capabilities, there is one important, but often-overlooked item: Many implementations fail to realize their full potential because they fall into the trap of building out just the proverbial shop window, and forgetting the actual shop!  It is just as important to add increased accessibility and flexibility to the underlying data-layer (and ease the access, discovery, and governance of your data), as it is to provide users the front-end thru powerful analytics and visualization capabilities. 

With respect to self‐service analytics, four phases can be identified in the market. These also typically mirror how analytics are implemented in many of companies. The following diagram describes in four phases how data virtualization can strengthen and enrich the self‐service data integration capabilities of tools for reporting and analytics:



To support both IT-driven and Business-driven BI, two techniques are required: data preparation, and data virtualization.   There are a many scenarios where you can use these techniques to strengthen and speedup the implementation of self‐service analytics:

  • Using data virtualization to operationalize user‐defined data sets
  • Using data virtualization as a data source for data preparation
  • Using data virtualization to make data sets developed with data preparation available for all users 

To learn about how to succeed in your data journey, feel free to contact us. More info about our full spectrum of data solutions is also available on the Datalumen website.

Read more in detail about the different scenario’s in the ‘Strengthening Self-Service Analytics with Data Preparation and Data Virtualization’ whitepaper. In addition, this whitepaper describes how these two BI forms can operate side by side in a cooperative fashion without lowering the level of self‐service for business users. In other words, it describes how the best of both worlds can be combined. This whitepaper is written by Rick Van Der Lans, an indepedent analyst and expert.